金融、技術、政策の修士号

Semester 1

September–December

Compulsory courses

• Financial Markets and Investment
• Financial Valuation
• フィンテックのインフラと政策
• Principles of Data Analytics
• Python Programming

Semester 2

January–May

Compulsory courses

• Introductory Applied Machine Learning
• Modern Financial Market Microstructure

オプションコース - 2つまたは3つを選択

• Blockchain, Governance and Policy
• Econometrics for Risk Analytics
• Economic Principles of Blockchain and Cryptocurrencies
• Ethics of Artificial Intelligence
• Financial Engineering
• Financial Machine Learning II (Practical)
• Investment Management
• Pattern Recognition in Financial Data
• Responsible Investing
• Technology Entrepreneurship and Commercialisation

Summer

May-August

Dissertation

Details of the Dissertation

As well as delivering a solid understanding of key theoretical finance and economic concepts, this Fintech MSc encourages potential future leaders to analyse and challenge the accepted financial setup.

Knowledge and understanding

By the end of the programme, students will be able to:

• Demonstrate an advanced knowledge of key theoretical finance and economic concepts underpinning financial markets
• Critically compare, contrast and evaluate the different machine learning techniques in terms of their applicability to solving problems in finance, this can be demonstrated by students using appropriate software to apply techniques to a given set of data
• Have an in-depth understanding of the relationships existing among the key global financial systems; for example, how bond yields dictate investment in equity and its derivatives
• Conduct valuation of financial instruments and projects within relevant regulatory contexts
• Trade financial instruments on exchanges/trading platforms by using state-of-the-art software packages and harnessing the power of relevant real-time financial data
• Demonstrate an appreciation of the role played by policies in shaping financial services delivery and financial markets
• Critically evaluate markets by being able to competently present arguments on the criticisms of the current set-up and offer the basis for the development of alternative technology-based markets and financial services products
• Demonstrate an appreciation of the social dimensions of technology use in financial markets

Graduate attributes

By the end of the programme, students will be able to:

• Demonstrate advanced numeracy and quantitative skills;
• 最新のオブジェクト指向プログラミング言語でのプログラミングに関する権威ある高度な知識を実証します。
• グループの一員として、または個人として、金融分野における研究上の質問/仮説を開発し、テストする能力を実証します。
• 関連するデータを識別し、関連する検索およびモデリングのスキルを実証します。
• 新規および既存の金融セクターの政策/規制イニシアチブから生じる機会を特定し、持続的に活用するために必要な批判的思考スキルと創意工夫を発揮します。
• データに基づく証拠に基づいて仮定や発言を評価する能力を実証します。
• 新しいアイデアに取り組み、利用可能なリソースを活用して誤った論理を検出できるようにします。
• さまざまな状況や構成を持つ聴衆に対して、適切にアイデアを伝え、交換します。
• 口頭だけでなく書面でも、合理的かつデータに基づいた議論を提示する
• 多様なグループ内で効果的に関わり、働きます。
• Effectively manage time and workload demands within a dynamic and challenging work environment.

Career Development

Graduates from the University of Edinburgh are highly sought after globally. Our dedicated Student Development Team within the Business School will be an integral part of your student experience from day one. We are here to help you become equipped to maximise your potential in the global market.

Graduate Employment

Potential roles available to graduates of this programme are varied across the finance sector, particularly in organisations exploiting big data. Examples of roles include:

• Data scientists
• Financial product developers/managers
• Financial/investment analysts
• Portfolio managers
• Quantitative regulatory analysts